Method and apparatus for point cloud compression

ABSTRACT

Aspects of the disclosure provide methods and apparatuses for point cloud compression and decompression. In some examples, an apparatus for point cloud compression/decompression includes processing circuitry. For example, the apparatus is for point cloud decompression. The processing circuitry decodes prediction information of an image from a coded bitstream corresponding to a point cloud. The prediction information indicates that the image includes a plurality of missed points from at least a patch for the point cloud, and the plurality of missed points are arranged in the image according to a non-jumpy scan. Then, the processing circuitry reconstructs the plurality of missed points from the image according to the non-jumpy scan.

INCORPORATION BY REFERENCE

This present application claims the benefit of priority to U.S.Provisional Application No. 62/812,952, “TECHNIQUES AND APPARATUS FORENHANCED MISSED POINTS CODING USING FLEXIBLE SCANNING FOR POINT CLOUDCOMPRESSION” filed on Mar. 1, 2019, which is incorporated by referenceherein in its entirety.

TECHNICAL FIELD

The present disclosure describes embodiments generally related to pointcloud compression.

BACKGROUND

The background description provided herein is for the purpose ofgenerally presenting the context of the disclosure. Work of thepresently named inventors, to the extent the work is described in thisbackground section, as well as aspects of the description that may nototherwise qualify as prior art at the time of filing, are neitherexpressly nor impliedly admitted as prior art against the presentdisclosure.

Various technologies are developed to capture and represent world, suchas objects in the world, environments in the world, and the like in3-dimensional (3D) space. 3D representations of the world can enablemore immersive forms of interaction and communication. Point clouds canbe used as 3D representation of the world. A point cloud is a set ofpoints in a 3D space, each with associated attributes, e.g. color,material properties, texture information, intensity attributes,reflectivity attributes, motion related attributes, modality attributes,and various other attributes. Such point clouds may include largeamounts of data and may be costly and time-consuming to store andtransmit.

SUMMARY

Aspects of the disclosure provide methods and apparatuses for pointcloud compression and decompression. In some examples, an apparatus forpoint cloud compression/decompression includes processing circuitry. Forexample, the apparatus is for point cloud decompression. The processingcircuitry decodes prediction information of an image from a codedbitstream corresponding to a point cloud. The prediction informationindicates that the image includes a plurality of missed points from atleast a patch for the point cloud, and the plurality of missed pointsare arranged in the image according to a non-jumpy scan. Then, theprocessing circuitry reconstructs the plurality of missed points fromthe image according to the non-jumpy scan.

In some embodiments, the processing circuitry reconstructs a firstmissed point as a last pixel in a first row, and a second missed pointthat is next to the first missed point as a first pixel in a second row.The last pixel in the first row and the first pixel in the second roware in a same column.

In some examples, the processing circuitry decodes a flag associatedwith the image, and the flag is indicative of the non-jumpy scan.

In some examples, the processing circuitry decodes a flag that isindicative of a block based non-jumpy scan and decodes a block size forthe block based non-jumpy scan. Then, the processing circuitry dividesthe image into blocks according to the block size, and reconstructsmissed points within a block according to the non-jumpy scan. In anexample, the processing circuitry reconstructs a first missed point as alast pixel in a first row of the block, and a second missed point thatis next to the first missed point as a first pixel in a second row ofthe block. The last pixel in the first row and the first pixel in thesecond row are in a same column. Further, the processing circuitryprocesses the blocks in an order according to the non-jumpy scan of theblocks.

According to some aspects of the disclosure, the apparatus is for pointcloud compression. The processing circuitry determines a plurality ofmissed points from at least a patch of a point cloud, and form an imagewith pixels associated with the plurality of missed points. A2-dimension distance between positions of two missed points in the imageis determined based on a 3-dimension distance between the two missedpoints in the point cloud. Further, the processing circuitry encodes theimage, and forms a coded bitstream that includes the encoded image.

In some embodiments, the processing circuitry orders the plurality ofmissed points into a list of missed points based on a nearest neighborcriterion, and associates the list of missed points to the pixels of theimage according to a non-jumpy scan.

In an embodiment, the processing circuitry associates a first missedpoint to a last pixel in a first row of the image, and associates asecond missed point that is next to the first missed point in the listof missed points to a first pixel in a second row of the image. The lastpixel in the first row and the first pixel in the second row are in asame column.

In another embodiment, the processing circuitry associates a firstmissed point to a last pixel in a first row of a block in the image, andassociates a second missed point that is next to the first missed pointin the list to a first pixel in a second row of the block in the image,the last pixel in the first row and the first pixel in the second rowbeing in a same column.

In an example, the processing circuitry includes a flag indicative ofthe non-jumpy scan in the coded bitstream. In another example, theprocessing circuitry includes a block size in the coded bitstream.

Aspects of the disclosure also provide a non-transitorycomputer-readable medium storing instructions which when executed by acomputer for point cloud compression/decompression cause the computer toperform the method for point cloud compression/decompression.

BRIEF DESCRIPTION OF THE DRAWINGS

Further features, the nature, and various advantages of the disclosedsubject matter will be more apparent from the following detaileddescription and the accompanying drawings in which:

FIG. 1 is a schematic illustration of a simplified block diagram of acommunication system (100) in accordance with an embodiment.

FIG. 2 is a schematic illustration of a simplified block diagram of astreaming system (200) in accordance with an embodiment.

FIG. 3 shows a block diagram of an encoder (300) for encoding pointcloud frames, according to some embodiments.

FIG. 4 shows a block diagram of a decoder for decoding a compressedbitstream corresponding to point cloud frames according to someembodiments.

FIG. 5 is a schematic illustration of a simplified block diagram of avideo decoder in accordance with an embodiment.

FIG. 6 is a schematic illustration of a simplified block diagram of avideo encoder in accordance with an embodiment.

FIG. 7 shows a diagram illustrating an arrangement of one-dimensional(1D) signal into a two-dimensional (2D) image.

FIG. 8 shows a diagram illustrating an arrangement of one-dimensional(1D) signal into a two-dimensional (2D) image.

FIG. 9 shows a diagram illustrating an arrangement of one-dimensional(1D) signal into a two-dimensional (2D) image.

FIG. 10 shows a syntax example according to some embodiments of thedisclosure.

FIG. 11 shows a flow chart outlining a process example according to someembodiments of the disclosure.

FIG. 12 shows a flow chart outlining a process example according to someembodiments of the disclosure.

FIG. 13 is a schematic illustration of a computer system in accordancewith an embodiment.

DETAILED DESCRIPTION OF EMBODIMENTS

Aspects of the disclosure provide point cloud coding techniques,specifically using video-coding for point cloud compression (V-PCC). TheV-PCC can utilize generic video codecs for point cloud compression. Thepoint cloud coding techniques in the present disclosure can improve bothlossless and lossy compression of missed points generated by the V-PCC.

Hereinafter, a point cloud generally may refer to a set of points in a3D space, each with associated attributes, e.g. color, materialproperties, texture information, intensity attributes, reflectivityattributes, motion related attributes, modality attributes, and variousother attributes. Point clouds can be used to reconstruct an object or ascene as a composition of such points. The points can be captured usingmultiple cameras and depth sensors in various setups and may be made upof thousands up to billions of points in order to realisticallyrepresent reconstructed scenes. A patch generally may refer to acontiguous subset of the surface described by the point cloud. A missedpoint generally may refer to a point not captured by the V-PCCprojection.

Compression technologies are needed to reduce the amount of datarequired to represent a point cloud. As such, technologies are neededfor lossy compression of point clouds for use in real-timecommunications and six Degrees of Freedom (6 DoF) virtual reality. Inaddition, technology is sought for lossless point cloud compression inthe context of dynamic mapping for autonomous driving and culturalheritage applications, and the like. Moving picture experts group (MPEG)starts working on a standard to address compression of geometry andattributes such as colors and reflectance, scalable/progressive coding,coding of sequences of point clouds captured over time, and randomaccess to subsets of the point cloud.

According to an aspect of the disclosure, the main philosophy behindV-PCC is to leverage existing video codecs to compress the geometry,occupancy, and texture of a dynamic point cloud as three separate videosequences. The extra metadata needed to interpret the three videosequences are compressed separately. A small portion of the overallbitstream is the metadata, which could be encoded/decoded efficientlyusing software implementation. The bulk of the information is handled bythe video codec.

FIG. 1 illustrates a simplified block diagram of a communication system(100) according to an embodiment of the present disclosure. Thecommunication system (100) includes a plurality of terminal devices thatcan communicate with each other, via, for example, a network (150). Forexample, the communication system (100) includes a pair of terminaldevices (110) and (120) interconnected via the network (150). In theFIG. 1 example, the first pair of terminal devices (110) and (120) thatperform unidirectional transmission of point cloud data. For example,the terminal device (110) may compress point cloud (e.g., pointsrepresenting a structure) that are captured by a sensor 105 connectedwith the terminal device (110). The compressed point cloud can betransmitted, for example in the form of a bitstream, to the otherterminal device (120) via the network (150). The terminal device (120)may receive the compressed point cloud from the network (150),decompress the bitstream to reconstruct the point cloud and suitablydisplay according to the reconstructed point cloud. Unidirectional datatransmission may be common in media serving applications and the like.

In the FIG. 1 example, the terminal devices (110) and (120) may beillustrated as servers, and personal computers, but the principles ofthe present disclosure may be not so limited. Embodiments of the presentdisclosure find application with laptop computers, tablet computers,smart phones, gaming terminals, media players and/or dedicatedthree-dimensional (3D) equipment. The network (150) represents anynumber of networks that transmit compressed point cloud between theterminal devices (110) and (120). The network (150) can include forexample wireline (wired) and/or wireless communication networks. Thenetwork (150) may exchange data in circuit-switched and/orpacket-switched channels. Representative networks includetelecommunications networks, local area networks, wide area networksand/or the Internet. For the purposes of the present discussion, thearchitecture and topology of the network (150) may be immaterial to theoperation of the present disclosure unless explained herein below.

FIG. 2 illustrates, as an example for an application for the disclosedsubject matter for point cloud. The disclosed subject matter can beequally applicable to other point cloud enabled applications, including,3D telepresence application, virtual reality application.

A streaming system 200 may include a capture subsystem (213). Thecapture subsystem (213) can include a point cloud source (201), forexample light detection and ranging (LIDAR) systems, 3D cameras, 3Dscanners, a graphics generation component that generates theuncompressed point cloud in software, and like that generates forexample point clouds (202) that are uncompressed. In an example, thepoint clouds (202) include points that are captured by the 3D cameras.The point clouds (202), depicted as a bold line to emphasize a high datavolume when compared to compressed point clouds (204) (a bitstream ofcompressed point clouds). The compressed point clouds (204) can begenerated by an electronic device (220) that includes an encoder (203)coupled to the point cloud source (201). The encoder (203) can includehardware, software, or a combination thereof to enable or implementaspects of the disclosed subject matter as described in more detailbelow. The compressed point clouds (204) (or bitstream of compressedpoint clouds (204)), depicted as a thin line to emphasize the lower datavolume when compared to the stream of point clouds (202), can be storedon a streaming server (205) for future use. One or more streaming clientsubsystems, such as client subsystems (206) and (208) in FIG. 2 canaccess the streaming server (205) to retrieve copies (207) and (209) ofthe compressed point cloud (204). A client subsystem (206) can include adecoder (210), for example, in an electronic device (230). The decoder(210) decodes the incoming copy (207) of the compressed point clouds andcreates an outgoing stream of reconstructed point clouds (211) that canbe rendered on a rendering device (212). In some streaming systems, thecompressed point clouds (204), (207), and (209) (e.g., bitstreams ofcompressed point clouds) can be compressed according to certainstandards. In some examples, video coding standards are used in thecompression of point clouds. Examples of those standards include, HighEfficiency Video Coding (HEVC), Versatile Video Coding (VVC), and thelike.

It is noted that the electronic devices (220) and (230) can includeother components (not shown). For example, the electronic device (220)can include a decoder (not shown) and the electronic device (230) caninclude an encoder (not shown) as well.

FIG. 3 shows a block diagram of a V-PCC encoder (300) for encoding pointcloud frames, according to some embodiments. In some embodiments, theV-PCC encoder (300) can be used in the communication system (100) andstreaming system (200). For example, the encoder (203) can be configuredand operate in a similar manner as the V-PCC encoder (300).

The V-PCC encoder (300) receives point cloud frames that areuncompressed inputs and generates bitstream corresponding to compressedpoint cloud frames. In some embodiments, the V-PCC encoder (300) mayreceive the point cloud frames from a point cloud source, such as thepoint cloud source (201) and the like.

In the FIG. 3 example, the V-PCC encoder (300) includes a patchgeneration module 306, a patch packing module 308, a geometry imagegeneration module 310, a texture image generation module 312, a patchinfo module 304, an occupancy map module 314, a smoothing module 336,image padding modules 316 and 318, a group dilation module 320, videocompression modules 322, 323 and 332, an auxiliary patch infocompression module 338, an entropy compression module 334 and amultiplexer 324 coupled together as shown in FIG. 3.

According to an aspect of the disclosure, the V-PCC encoder (300),converts 3D point cloud frames into an image-based representation alongwith some meta data (e.g., occupancy map and patch info) necessary toconvert the compressed point cloud back into a decompressed point cloud.In some examples, the V-PCC encoder (300) can convert 3D point cloudframes into geometry images, texture images and occupancy maps, and thenuse video coding techniques to encode the geometry images, textureimages and occupancy maps into a bitstream.

The patch generation module (306) segments a point cloud into a set ofpatches (e.g., a patch is defined as a contiguous subset of the surfacedescribed by the point cloud), which may be overlapping or not, suchthat each patch may be described by a depth field with respect to aplane in 2D space. In some embodiments, the patch generation module(306) aims at decomposing the point cloud into a minimum number ofpatches with smooth boundaries, while also minimizing the reconstructionerror.

The patch info module (304) can collect the patch information thatindicates sizes and shapes of the patches. In some examples, the patchinformation can be packed into an image frame and then encoded by theauxiliary patch info compression module 338 to generate the compressedauxiliary patch information.

The patch packing module 308 is configured to map the extracted patchesonto a 2 dimensional (2D) grid while minimize the unused space andguarantee that every M×M (e.g., 16×16) block of the grid is associatedwith a unique patch. Efficient patch packing can directly impact thecompression efficiency either by minimizing the unused space or ensuringtemporal consistency.

The geometry image generation module (310) can generate 2D geometryimages associated with geometry of the point cloud at given patchlocations. The texture image generation module (312) can generate 2Dtexture images associated with texture of the point cloud at given patchlocations. The geometry image generation module 310 and the textureimage generation module (312) exploit the 3D to 2D mapping computedduring the packing process to store the geometry and texture of thepoint cloud as images. In order to better handle the case of multiplepoints being projected to the same sample, each patch is projected ontotwo images, referred to as layers. In an example, geometry image isrepresented by a monochromatic frame of W×H in YUV420-8 bit format. Togenerate the texture image, the texture generation procedure exploitsthe reconstructed/smoothed geometry in order to compute the colors to beassociated with the re-sampled points.

The occupancy map module 314 can generate an occupancy map thatdescribes padding information at each unit. For example, the occupancyimage includes of a binary map that indicates for each cell of the gridwhether the cell belongs to the empty space or to the point cloud. In anexample, the occupancy map uses binary information describing for eachpixel whether the pixel is padded or not. In another example, theoccupancy map uses binary information describing for each block ofpixels whether the block of pixels is padded or not.

The occupancy map generated by the occupancy map module 314 can becompressed using lossless coding or lossy coding. When lossless codingis used, the entropy compression module 334 is used to compress theoccupancy map; when lossy coding is used, the video compression module332 is used to compress the occupancy map.

It is noted that the patch packing module 308 may leave some emptyspaces between 2D patches packed in an image frame. The image paddingmodule 316 and 318 can fill the empty spaces (referred to as padding) inorder to generate an image frame that may be suited for 2D video andimage codecs. The image padding is also referred to as backgroundfilling which can fill the unused space by redundant information. Insome examples, a good background filling minimally increases the bitrate while does not introduce significant coding distortion around thepatch boundaries.

The video compression modules 322, 323 and 332 can encode the 2D images,such as the padded geometry images, padded texture images, and occupancymaps based on a suitable video coding standard, such as HEVC, VVC andthe like. In an example, the video compression modules 322, 323 and 332are individual components that operate separately. It is noted that thevideo compression modules 322, 323 and 332 can be implemented as asingle component in another example.

In some examples, the smoothing module 336 is configured to generate asmoothed image of the reconstructed geometry image. The smoothed imageinformation can be provided to the texture image generation 312. Then,the texture image generation 312 may adjust the generation of thetexture image based on the reconstructed geometry images. For example,when a patch shape (e.g. geometry) is slightly distorted during encodingand decoding, the distortion may be taken into account when generatingthe texture images to correct for the distortion in patch shape.

In some embodiments, the group dilation 320 is configured to pad pixelsaround the object boundaries with redundant low-frequency content inorder to improve coding gain as well as visual quality of reconstructedpoint cloud.

The multiplexer 324 can multiplex the compressed geometry image, thecompressed texture image, the compressed occupancy map, the compressedauxiliary patch information into a compressed bitstream.

FIG. 4 shows a block diagram of a V-PCC decoder (400) for decodingcompressed bitstream corresponding to point cloud frames, according tosome embodiments. In some embodiments, the V-PCC decoder (400) can beused in the communication system (100) and streaming system (200). Forexample, the decoder (210) can be configured and operate in a similarmanner as the V-PCC decoder (400). The V-PCC decoder (400) receives thecompressed bitstream, and generates reconstructed point cloud based onthe compressed bitstream.

In the FIG. 4 example, the V-PCC decoder (400) includes a de-multiplexer(432), video decompression modules (434) and (436), an occupancy mapdecompression module (438), an auxiliary patch-information decompressionmodule (442), a geometry reconstruction module (444), a smoothing module(446), a texture reconstruction module (448) and a color smoothingmodule (452) coupled together as shown in FIG. 4.

The de-multiplexer (432) can receive the compressed bitstream andseparate into compressed texture image, compressed geometry image,compressed occupancy map and compressed auxiliary patch information.

The video decompression modules (434) and (436) can decode thecompressed images according to suitable standard (e.g., HEVC, VVC, etc.)and output decompressed images. For example, the video decompressionmodule (434) decodes the compressed texture images and outputsdecompressed texture images; and the video decompression module (436)decodes the compressed geometry images and outputs the decompressedgeometry images.

The occupancy map decompression module (438) can decode the compressedoccupancy maps according to suitable standard (e.g., HEVC, VVC, etc.)and output decompressed occupancy maps.

The auxiliary patch-information decompression module (442) can decodethe compressed auxiliary patch information according to suitablestandard (e.g., HEVC, VVC, etc.) and output decompressed auxiliary patchinformation.

The geometry reconstruction module (444) can receive the decompressedgeometry images, and generate reconstructed point cloud geometry basedon the decompressed occupancy map and decompressed auxiliary patchinformation.

The smoothing module (446) can smooth incongruences at edges of patches.The smoothing procedure aims at alleviating potential discontinuitiesthat may arise at the patch boundaries due to compression artifacts. Insome embodiments, a smoothing filter may be applied to the pixelslocated on the patch boundaries to alleviate the distortions that may becaused by the compression/decompression.

The texture reconstruction module (448) can determine textureinformation for points in the point cloud based on the decompressedtexture images and the smoothing geometry.

The color smoothing module (452) can smooth incongruences of coloring.Non-neighboring patches in 3D space are often packed next to each otherin 2D videos. In some examples, pixel values from non-neighboringpatches might be mixed up by the block-based video codec. The goal ofcolor smoothing is to reduce the visible artifacts that appear at patchboundaries.

FIG. 5 shows a block diagram of a video decoder (510) according to anembodiment of the present disclosure. The video decoder (510) can beused in the V-PCC decoder (400). For example, the video decompressionmodules (434) and (436), the occupancy map decompression module (438)can be similarly configured as the video decoder (510).

The video decoder (510) may include a parser (520) to reconstructsymbols (521) from compressed images, such as the coded video sequence.Categories of those symbols include information used to manage operationof the video decoder (510). The parser (520) may parse/entropy-decodethe coded video sequence that is received. The coding of the coded videosequence can be in accordance with a video coding technology orstandard, and can follow various principles, including variable lengthcoding, Huffman coding, arithmetic coding with or without contextsensitivity, and so forth. The parser (520) may extract from the codedvideo sequence, a set of subgroup parameters for at least one of thesubgroups of pixels in the video decoder, based upon at least oneparameter corresponding to the group. Subgroups can include Groups ofPictures (GOPs), pictures, tiles, slices, macroblocks, Coding Units(CUs), blocks, Transform Units (TUs), Prediction Units (PUs) and soforth. The parser (520) may also extract from the coded video sequenceinformation such as transform coefficients, quantizer parameter values,motion vectors, and so forth.

The parser (520) may perform an entropy decoding/parsing operation onthe video sequence received from a buffer memory, so as to createsymbols (521).

Reconstruction of the symbols (521) can involve multiple different unitsdepending on the type of the coded video picture or parts thereof (suchas: inter and intra picture, inter and intra block), and other factors.Which units are involved, and how, can be controlled by the subgroupcontrol information that was parsed from the coded video sequence by theparser (520). The flow of such subgroup control information between theparser (520) and the multiple units below is not depicted for clarity.

Beyond the functional blocks already mentioned, the video decoder (510)can be conceptually subdivided into a number of functional units asdescribed below. In a practical implementation operating undercommercial constraints, many of these units interact closely with eachother and can, at least partly, be integrated into each other. However,for the purpose of describing the disclosed subject matter, theconceptual subdivision into the functional units below is appropriate.

A first unit is the scaler/inverse transform unit (551). Thescaler/inverse transform unit (551) receives a quantized transformcoefficient as well as control information, including which transform touse, block size, quantization factor, quantization scaling matrices,etc. as symbol(s) (521) from the parser (520). The scaler/inversetransform unit (551) can output blocks comprising sample values, thatcan be input into aggregator (555).

In some cases, the output samples of the scaler/inverse transform (551)can pertain to an intra coded block; that is: a block that is not usingpredictive information from previously reconstructed pictures, but canuse predictive information from previously reconstructed parts of thecurrent picture. Such predictive information can be provided by an intrapicture prediction unit (552). In some cases, the intra pictureprediction unit (552) generates a block of the same size and shape ofthe block under reconstruction, using surrounding already reconstructedinformation fetched from the current picture buffer (558). The currentpicture buffer (558) buffers, for example, partly reconstructed currentpicture and/or fully reconstructed current picture. The aggregator(555), in some cases, adds, on a per sample basis, the predictioninformation the intra prediction unit (552) has generated to the outputsample information as provided by the scaler/inverse transform unit(551).

In other cases, the output samples of the scaler/inverse transform unit(551) can pertain to an inter coded, and potentially motion compensatedblock. In such a case, a motion compensation prediction unit (553) canaccess reference picture memory (557) to fetch samples used forprediction. After motion compensating the fetched samples in accordancewith the symbols (521) pertaining to the block, these samples can beadded by the aggregator (555) to the output of the scaler/inversetransform unit (551) (in this case called the residual samples orresidual signal) so as to generate output sample information. Theaddresses within the reference picture memory (557) from where themotion compensation prediction unit (553) fetches prediction samples canbe controlled by motion vectors, available to the motion compensationprediction unit (553) in the form of symbols (521) that can have, forexample X, Y, and reference picture components. Motion compensation alsocan include interpolation of sample values as fetched from the referencepicture memory (557) when sub-sample exact motion vectors are in use,motion vector prediction mechanisms, and so forth.

The output samples of the aggregator (555) can be subject to variousloop filtering techniques in the loop filter unit (556). Videocompression technologies can include in-loop filter technologies thatare controlled by parameters included in the coded video sequence (alsoreferred to as coded video bitstream) and made available to the loopfilter unit (556) as symbols (521) from the parser (520), but can alsobe responsive to meta-information obtained during the decoding ofprevious (in decoding order) parts of the coded picture or coded videosequence, as well as responsive to previously reconstructed andloop-filtered sample values.

The output of the loop filter unit (556) can be a sample stream that canbe output to a render device as well as stored in the reference picturememory (557) for use in future inter-picture prediction.

Certain coded pictures, once fully reconstructed, can be used asreference pictures for future prediction. For example, once a codedpicture corresponding to a current picture is fully reconstructed andthe coded picture has been identified as a reference picture (by, forexample, the parser (520)), the current picture buffer (558) can becomea part of the reference picture memory (557), and a fresh currentpicture buffer can be reallocated before commencing the reconstructionof the following coded picture.

The video decoder (510) may perform decoding operations according to apredetermined video compression technology in a standard, such as ITU-TRec. H.265. The coded video sequence may conform to a syntax specifiedby the video compression technology or standard being used, in the sensethat the coded video sequence adheres to both the syntax of the videocompression technology or standard and the profiles as documented in thevideo compression technology or standard. Specifically, a profile canselect certain tools as the only tools available for use under thatprofile from all the tools available in the video compression technologyor standard. Also necessary for compliance can be that the complexity ofthe coded video sequence is within bounds as defined by the level of thevideo compression technology or standard. In some cases, levels restrictthe maximum picture size, maximum frame rate, maximum reconstructionsample rate (measured in, for example megasamples per second), maximumreference picture size, and so on. Limits set by levels can, in somecases, be further restricted through Hypothetical Reference Decoder(HRD) specifications and metadata for HRD buffer management signaled inthe coded video sequence.

FIG. 6 shows a block diagram of a video encoder (603) according to anembodiment of the present disclosure. The video encoder (603) can beused in the V-PCC encoder (300) the compresses point clouds. In anexample, the video compression module (322) and (323), and the videocompression module (332) are configured similarly to the encoder (603).

The video encoder (603) may receive images, such as padded geometryimages, padded texture images and the like, and generate compressedimages.

According to an embodiment, the video encoder (603) may code andcompress the pictures of the source video sequence (images) into a codedvideo sequence (compressed images) in real time or under any other timeconstraints as required by the application. Enforcing appropriate codingspeed is one function of a controller (650). In some embodiments, thecontroller (650) controls other functional units as described below andis functionally coupled to the other functional units. The coupling isnot depicted for clarity. Parameters set by the controller (650) caninclude rate control related parameters (picture skip, quantizer, lambdavalue of rate-distortion optimization techniques, . . . ), picture size,group of pictures (GOP) layout, maximum motion vector search range, andso forth. The controller (650) can be configured to have other suitablefunctions that pertain to the video encoder (603) optimized for acertain system design.

In some embodiments, the video encoder (603) is configured to operate ina coding loop. As an oversimplified description, in an example, thecoding loop can include a source coder (630) (e.g., responsible forcreating symbols, such as a symbol stream, based on an input picture tobe coded, and a reference picture(s)), and a (local) decoder (633)embedded in the video encoder (603). The decoder (633) reconstructs thesymbols to create the sample data in a similar manner as a (remote)decoder also would create (as any compression between symbols and codedvideo bitstream is lossless in the video compression technologiesconsidered in the disclosed subject matter). The reconstructed samplestream (sample data) is input to the reference picture memory (634). Asthe decoding of a symbol stream leads to bit-exact results independentof decoder location (local or remote), the content in the referencepicture memory (634) is also bit exact between the local encoder andremote encoder. In other words, the prediction part of an encoder “sees”as reference picture samples exactly the same sample values as a decoderwould “see” when using prediction during decoding. This fundamentalprinciple of reference picture synchronicity (and resulting drift, ifsynchronicity cannot be maintained, for example because of channelerrors) is used in some related arts as well.

The operation of the “local” decoder (633) can be the same as of a“remote” decoder, such as the video decoder (510), which has alreadybeen described in detail above in conjunction with FIG. 5. Brieflyreferring also to FIG. 5, however, as symbols are available andencoding/decoding of symbols to a coded video sequence by an entropycoder (645) and the parser (520) can be lossless, the entropy decodingparts of the video decoder (510), including and parser (520) may not befully implemented in the local decoder (633).

An observation that can be made at this point is that any decodertechnology except the parsing/entropy decoding that is present in adecoder also necessarily needs to be present, in substantially identicalfunctional form, in a corresponding encoder. For this reason, thedisclosed subject matter focuses on decoder operation. The descriptionof encoder technologies can be abbreviated as they are the inverse ofthe comprehensively described decoder technologies. Only in certainareas a more detail description is required and provided below.

During operation, in some examples, the source coder (630) may performmotion compensated predictive coding, which codes an input picturepredictively with reference to one or more previously-coded picture fromthe video sequence that were designated as “reference pictures”. In thismanner, the coding engine (632) codes differences between pixel blocksof an input picture and pixel blocks of reference picture(s) that may beselected as prediction reference(s) to the input picture.

The local video decoder (633) may decode coded video data of picturesthat may be designated as reference pictures, based on symbols createdby the source coder (630). Operations of the coding engine (632) mayadvantageously be lossy processes. When the coded video data may bedecoded at a video decoder (not shown in FIG. 6), the reconstructedvideo sequence typically may be a replica of the source video sequencewith some errors. The local video decoder (633) replicates decodingprocesses that may be performed by the video decoder on referencepictures and may cause reconstructed reference pictures to be stored inthe reference picture cache (634). In this manner, the video encoder(603) may store copies of reconstructed reference pictures locally thathave common content as the reconstructed reference pictures that will beobtained by a far-end video decoder (absent transmission errors).

The predictor (635) may perform prediction searches for the codingengine (632). That is, for a new picture to be coded, the predictor(635) may search the reference picture memory (634) for sample data (ascandidate reference pixel blocks) or certain metadata such as referencepicture motion vectors, block shapes, and so on, that may serve as anappropriate prediction reference for the new pictures. The predictor(635) may operate on a sample block-by-pixel block basis to findappropriate prediction references. In some cases, as determined bysearch results obtained by the predictor (635), an input picture mayhave prediction references drawn from multiple reference pictures storedin the reference picture memory (634).

The controller (650) may manage coding operations of the source coder(630), including, for example, setting of parameters and subgroupparameters used for encoding the video data.

Output of all aforementioned functional units may be subjected toentropy coding in the entropy coder (645). The entropy coder (645)translates the symbols as generated by the various functional units intoa coded video sequence, by lossless compressing the symbols according totechnologies such as Huffman coding, variable length coding, arithmeticcoding, and so forth.

The controller (650) may manage operation of the video encoder (603).During coding, the controller (650) may assign to each coded picture acertain coded picture type, which may affect the coding techniques thatmay be applied to the respective picture. For example, pictures oftenmay be assigned as one of the following picture types:

An Intra Picture (I picture) may be one that may be coded and decodedwithout using any other picture in the sequence as a source ofprediction. Some video codecs allow for different types of intrapictures, including, for example Independent Decoder Refresh (“IDR”)Pictures. A person skilled in the art is aware of those variants of Ipictures and their respective applications and features.

A predictive picture (P picture) may be one that may be coded anddecoded using intra prediction or inter prediction using at most onemotion vector and reference index to predict the sample values of eachblock.

A bi-directionally predictive picture (B Picture) may be one that may becoded and decoded using intra prediction or inter prediction using atmost two motion vectors and reference indices to predict the samplevalues of each block. Similarly, multiple-predictive pictures can usemore than two reference pictures and associated metadata for thereconstruction of a single block.

Source pictures commonly may be subdivided spatially into a plurality ofsample blocks (for example, blocks of 4×4, 8×8, 4×8, or 16×16 sampleseach) and coded on a block-by-block basis. Blocks may be codedpredictively with reference to other (already coded) blocks asdetermined by the coding assignment applied to the blocks' respectivepictures. For example, blocks of I pictures may be codednon-predictively or they may be coded predictively with reference toalready coded blocks of the same picture (spatial prediction or intraprediction). Pixel blocks of P pictures may be coded predictively, viaspatial prediction or via temporal prediction with reference to onepreviously coded reference picture. Blocks of B pictures may be codedpredictively, via spatial prediction or via temporal prediction withreference to one or two previously coded reference pictures.

The video encoder (603) may perform coding operations according to apredetermined video coding technology or standard, such as ITU-T Rec.H.265. In its operation, the video encoder (603) may perform variouscompression operations, including predictive coding operations thatexploit temporal and spatial redundancies in the input video sequence.The coded video data, therefore, may conform to a syntax specified bythe video coding technology or standard being used.

A video may be in the form of a plurality of source pictures (images) ina temporal sequence. Intra-picture prediction (often abbreviated tointra prediction) makes use of spatial correlation in a given picture,and inter-picture prediction makes uses of the (temporal or other)correlation between the pictures. In an example, a specific pictureunder encoding/decoding, which is referred to as a current picture, ispartitioned into blocks. When a block in the current picture is similarto a reference block in a previously coded and still buffered referencepicture in the video, the block in the current picture can be coded by avector that is referred to as a motion vector. The motion vector pointsto the reference block in the reference picture, and can have a thirddimension identifying the reference picture, in case multiple referencepictures are in use.

In some embodiments, a bi-prediction technique can be used in theinter-picture prediction. According to the bi-prediction technique, tworeference pictures, such as a first reference picture and a secondreference picture that are both prior in decoding order to the currentpicture in the video (but may be in the past and future, respectively,in display order) are used. A block in the current picture can be codedby a first motion vector that points to a first reference block in thefirst reference picture, and a second motion vector that points to asecond reference block in the second reference picture. The block can bepredicted by a combination of the first reference block and the secondreference block.

Further, a merge mode technique can be used in the inter-pictureprediction to improve coding efficiency.

According to some embodiments of the disclosure, predictions, such asinter-picture predictions and intra-picture predictions are performed inthe unit of blocks. For example, according to the HEVC standard, apicture in a sequence of video pictures is partitioned into coding treeunits (CTU) for compression, the CTUs in a picture have the same size,such as 64×64 pixels, 32×32 pixels, or 16×16 pixels. In general, a CTUincludes three coding tree blocks (CTBs), which are one luma CTB and twochroma CTBs. Each CTU can be recursively quadtree split into one ormultiple coding units (CUs). For example, a CTU of 64×64 pixels can besplit into one CU of 64×64 pixels, or 4 CUs of 32×32 pixels, or 16 CUsof 16×16 pixels. In an example, each CU is analyzed to determine aprediction type for the CU, such as an inter prediction type or an intraprediction type. The CU is split into one or more prediction units (PUs)depending on the temporal and/or spatial predictability. Generally, eachPU includes a luma prediction block (PB), and two chroma PBs. In anembodiment, a prediction operation in coding (encoding/decoding) isperformed in the unit of a prediction block. Using a luma predictionblock as an example of a prediction block, the prediction block includesa matrix of values (e.g., luma values) for pixels, such as 8×8 pixels,16×16 pixels, 8×16 pixels, 16×8 pixels, and the like.

According to some aspects of the disclosure, due to occlusion, the V-PCCprojection approach may not capture every point, and the points that aremissed by the V-PCC projection approach are referred to as missedpoints. In some examples, the missed points typically belong to randomlocations in 3D space and lack high geometry and color correlations. Insome examples, V-PCC collects the missed points and creates two of onedimensional (1D) signals, such as a geometry signal and a color signalthat are respectively one dimensional signals. Further, each of these 1Dsignals can be arranged in a separate 2D image and compressed by HEVCafterwards in some examples. The present disclosure provide techniquesfor the arrangements of the 1D signals into 2D images that are amenablefor 2D compression tools (like HEVC).

The proposed methods may be used separately or combined in any order.Further, each of the methods (or embodiments), encoder, and decoder maybe implemented by processing circuitry (e.g., one or more processors orone or more integrated circuits). In one example, the one or moreprocessors execute a program that is stored in a non-transitorycomputer-readable medium.

In some examples, after the patch generation, V-PCC scans missed pointsfrom the patches in 3D and puts geometry and color values of the missedpoints into two separate images. In an example, a Kd-tree is createdover the missed points and the missed points are scanned to form 1Dsignals based on the nearest neighborhood criteria. The scanning resultincludes a geometry signal and a color signal that are respectively onedimensional. For example, the missed points are sorted according to thescan of the Kd-tree based on the nearest neighborhood criteria. Thegeometry signal includes a sequence of geometry samples for the sortedmissed points, and the color signal includes a sequence of color valuesfor the sorted missed points. In some portions of the presentdisclosure, the geometry signal is used as an example for ease ofdescription of techniques, and the disclosed techniques on the geometrysignal can be similarly used on the color signal.

FIG. 7 shows a diagram illustrating an arrangement (700) of a geometrysignal of 1D into a two-dimensional (2D) image. In the FIG. 7 example,squares represent pixels of the image (either geometry or texture image)for the missed points. Samples (corresponding to the missed points) areput in each row starting from the beginning of the row to the end. Thereis jump (a relatively large distance between adjacent samples) betweenconsecutive rows.

Specifically, in the FIG. 7 example, the geometry signal is arrangedinto a 2D image following an order of arrow lines (710), (720), (730),(740), (750), (760), (770) and (780). Specifically, arrow line (710)indicates an arrangement of the first 12 geometry samples in thegeometry signal into a first row of pixels of the 2D image from left toright; arrow line (720) indicates an arrangement of the second 12geometry samples in the geometry signal into a second row of pixels ofthe 2D image from left to right; arrow line (730) indicates anarrangement of the third 12 geometry samples in the geometry signal intoa third row of pixels of the 2D image from left to right; arrow line(740) indicates an arrangement of the fourth 12 geometry samples in thegeometry signal into a fourth row of pixels of the 2D image from left toright; arrow line (750) indicates an arrangement of the fifth 12geometry samples in the geometry signal into a fifth row of pixels ofthe 2D image from left to right; arrow line (760) indicates anarrangement of the sixth 12 geometry samples in the geometry signal intoa sixth row of pixels of the 2D image from left to right; arrow line(770) indicates an arrangement of the seventh 12 geometry samples in thegeometry signal into a seventh row of pixels of the 2D image from leftto right; and arrow line (780) indicates an arrangement of the eighth 12geometry samples in the geometry signal into an eighth row of pixels ofthe 2D image from left to right.

In the FIG. 7 example, the arrow lines (710), (720), (730), (740),(750), (760), (770) and (780) correspond to horizontal scan order forarranging the geometry samples in the geometry signal. All of the arrowlines (710), (720), (730), (740), (750), (760), (770) and (780) are fromleft to right. When adjacent geometry samples in the 1D geometry signalare disposed at pixels in the same row, the horizontal difference of thepixels is 1. However, when adjacent geometry samples in the 1D geometrysignal are placed at pixels in different rows, the pixels havesignificant horizontal difference (e.g., greater than 1). For example,the 12th geometry sample in the 1D geometry signal is placed at the lastpixel in the first row, the 13th geometry sample in the 1D geometrysignal is placed at the first pixel in the second row, and thehorizontal difference of the two pixels is 11 (also referred to as ahorizontal jump of 11). The order in FIG. 7 is referred to as a jumpyhorizontal raster scan order. Specifically, the order in FIG. 7 has 7jumps of 11 that are shown as dash lines.

It is noted that while 2D image in FIG. 7 has eight rows and each rowhas 12 pixels, the technique can be used in a 2D image of any suitablenumber of rows and any suitable number of pixels in each row.

According to some aspects of the disclosure, neighboring values in thegeometry (color) signal may correspond to geometry samples of nearbymissed points, and thus maybe close. Thus, arranging neighboring valuesof the 1D signal in neighborhood region of the 2D image may result insimilar values for pixels in the neighborhood region, and can result inimprovement of 2D image coding efficiency of both lossless and lossycases.

FIG. 8 shows a diagram illustrating an arrangement (800) of a geometrysignal of 1D into a two-dimensional (2D) image. In the FIG. 8 example,squares represent pixels of the image (either geometry or texture image)for the missed points. Jumps between consecutive rows are minimal andcorrelated samples are kept close together. Generally, when anarrangement assigns any two consecutive samples in a 1D signal to twoneighboring units (e.g., pixels, blocks and the like) in the 2D image,the arrangement is referred to as a non-jumpy scan. The two neighboringunits can be neighbors in a same row of units or neighbors in a samecolumn of units.

Specifically, in the FIG. 8 example, the geometry signal is arrangedinto a 2D image following an order of arrow lines (810), (820), (830),(840), (850), (860), (870) and (880). Specifically, arrow line (810)indicates an arrangement of the first 12 geometry samples in thegeometry signal into a first row of pixels of the 2D image from left toright; arrow line (820) indicates an arrangement of the second 12geometry samples in the geometry signal into a second row of pixels ofthe 2D image from right to left; arrow line (830) indicates anarrangement of the third 12 geometry samples in the geometry signal intoa third row of pixels of the 2D image from left to right; arrow line(840) indicates an arrangement of the fourth 12 geometry samples in thegeometry signal into a fourth row of pixels of the 2D image from rightto left; arrow line (850) indicates an arrangement of the fifth 12geometry samples in the geometry signal into a fifth row of pixels ofthe 2D image from left to right; arrow line (860) indicates anarrangement of the sixth 12 geometry samples in the geometry signal intoa sixth row of pixels of the 2D image from right to left; arrow line(870) indicates an arrangement of the seventh 12 geometry samples in thegeometry signal into a seventh row of pixels of the 2D image from leftto right; and arrow line (880) indicates an arrangement of the eighth 12geometry samples in the geometry signal into an eighth row of pixels ofthe 2D image from right to left.

In the FIG. 8 example, the arrow lines (810), (820), (830), (840),(850), (860), (870) and (880) correspond to horizontal scan order forarranging the geometry samples in the geometry signal. The arrow lines(810), (820), (830), (840), (850), (860), (870) and (880) alternate thescan directions. In the FIG. 8 example, adjacent geometry samples in the1D geometry signal are disposed in pixels in the 2D images as horizontalneighbors or vertical neighbors. When adjacent geometry samples in the1D geometry signal are disposed at pixels in the same row, the adjacentgeometry samples are horizontal neighbors, and the horizontal differenceof the pixels is 1. When adjacent geometry samples in the 1D geometrysignal are placed at pixels in different rows, the pixels have samehorizontal value and the vertical difference is 1, and are verticalneighbors. For example, the 12th geometry sample in the 1D geometrysignal is placed at the last pixel in the first row, the 13th geometrysample in the 1D geometry signal is placed at the last pixel in thesecond row, and the horizontal difference of the two pixels is 0 and thevertical difference of the two pixel is 1. The order in FIG. 8 isreferred to as a non-jumpy horizontal raster scan order.

It is noted that while 2D image in FIG. 8 has eight rows and each rowhas 12 pixels, the technique can be used in a 2D image of any suitablenumber of rows and any suitable number of pixels in each row.

According to an aspect of the disclosure, using the non-jumpy horizontalraster scan order, the more correlated samples in 3D space (which arecloser together in 3D) are placed in closer pixels in the 2D image. Thisplacement can improve the performance of prediction tools adopted invideo compression codecs.

FIG. 9 shows a diagram illustrating an arrangement (900) of a geometrysignal of 1D into a two-dimensional (2D) image. In the FIG. 9 example,squares represent pixels of the image (either geometry or texture image)for the missed points. In this example, the image is divided into blocksof size 4×4. These blocks are scanned in non-jumpy scan order. Inaddition, inside each block, samples are scanned in non-jumpy scanorder.

In the FIG. 9 example, a 2D image is divided into blocks of squareshapes. Samples of the 1D geometry signals are disposed to the blocks ina non-jumpy horizontal raster order of the blocks. Further, within eachblock, samples are disposed on the pixels following the non-jumpyhorizontal raster scan order.

Specifically, the 2D image is divided into blocks (910), (920), (930),(940), (950) and (960), and each block has 4×4 pixels. Samples in thegeometry signal are disposed to the blocks in an order of block (910),block (920), block (930), block (940), block (950) and block (960).Within block (910), samples of the geometry signal are arrangedfollowing a non-jumpy horizontal raster scan order, such as shown by thearrow lines (911), (912), (913) and (914). Within block (920), samplesof the geometry signal are arranged following a non-jumpy horizontalraster scan order, such as shown by the arrow lines (921), (922), (923)and (924). Within block (930), samples of the geometry signal arearranged following a non-jumpy horizontal raster scan order, such asshown by the arrow lines (931), (932), (933) and (934). Within block(940), samples of the geometry signal are arranged following a non-jumpyhorizontal raster scan order, such as shown by the arrow lines (941),(942), (943) and (944). Within block (950), samples of the geometrysignal are arranged following a non-jumpy horizontal raster scan order,such as shown by the arrow lines (951), (952), (953) and (954). Withinblock (960), samples of the geometry signal are arranged following anon-jumpy horizontal raster scan order, such as shown by the arrow lines(961), (962), (963) and (964).

It is noted that while the 2D image is divided into 4×4 blocks in theFIG. 9 examples, other suitable N×N blocks (e.g. 64×64, 32×32, etc.) canbe used. The non-jumpy scan order shown in FIG. 9 is referred to asblock based non-jumpy horizontal raster scan order.

It is noted that the scan orders shown in FIGS. 7-9 can be used at theencoder side to form the image for the missed points, and can be used atthe decoder side to decode the missed points from the coded bitstream.

In some embodiments, the arrangements of the samples for the missedpoints can be flexible and not dependent on the codec. For example, thecompression tools for 2D operate by regions, such as coding units (CUs).In an example, a set of consecutive samples (corresponding to missedpoints) is disposed in a CU. Further, samples (corresponding to missedpoints) within a region (e.g., CU) are arranged in a way such thatsamples closer in 3D are put in neighboring locations in 2D. Thearrangement could be signaled (e.g., by flags in the coded bitstream)from the encoder side to the decoder side.

In some embodiments, one or more flags can be used. In an example,non_jumpy_raster_scan_present_flag is used to indicate whether non-jumpyraster scan is used or not. For example, whennon_jumpy_raster_scan_present_flag is true, non-jumpy raster scan may beused; and when non_jumpy_raster_scan_present_flag is false, non-jumpyraster scan is not used. Further, block_based_scan_present_flag is usedto indicate whether the image is divided into blocks or not forscanning. For example, when block_based_scan_present_flag is true, theimage is divided into blocks for scanning; and whenblock_based_scan_present_flag is false, the image is not divided intoblocks for scanning. Further, non_jumpy_raster_scan is used to indicatewhether the non-jumpy raster scan is enabled or not. For example, whennon_jumpy_raster_scan is true, non jumpy raster scan is enabled, andwhen non_jumpy_raster_scan is false, non jumpy raster scan is disabled.Further, in an embodiment, other suitable information related to thenon-jumpy scan can be included in the coded bitstream. For example,block size is used to indicate the size of the blocks for block basednon-jumpy raster scan. The value of block_size is in the range [0,2¹⁶−1] in an example.

FIG. 10 shows a syntax example according to some embodiments of thedisclosure. In the FIG. 10 example, when flexible missed point scan isenabled (e.g., flexible_missed_points_scan_enabled_flag is true), twoflags non_jumpy_raster_scan_present_flag andblock_based_scan_present_flag are coded (encoded at the encoder side ordecoded at the decoder side). When non_jumpy_raster_scan_present_flag istrue, non_jumpy_raster_scan is coded (encoded at the encoder side ordecoded at the decoder side). When block_based_scan_present_flag istrue, block size is coded (encoded at the encoder side or decoded at thedecoder side).

In an example, at the decoder side, when non_jumpy_raster_scan is true,the decoder can decode the image for missed points according to the scanorder in FIG. 8. When the block_based_scan_present_flag is true, thedecoder decodes block_size and scans the samples according to the orderin FIG. 9.

FIG. 11 shows a flow chart outlining a process (1100) according to anembodiment of the disclosure. The process (1100) can be used during anencoding process for encoding point clouds. In various embodiments, theprocess (1100) is executed by processing circuitry, such as theprocessing circuitry in the terminal devices (110), the processingcircuitry that performs functions of the encoder (203), the processingcircuitry that performs functions of the encoder (300), and the like. Insome embodiments, the process (1100) is implemented in softwareinstructions, thus when the processing circuitry executes the softwareinstructions, the processing circuitry performs the process (1100). Theprocess starts at (S1101) and proceeds to (S1110).

At (S1110), missed points are determined. In some examples, after thepatch generation, missed points from the patches in 3D point clouds aredetermined.

At (S1120), an image with pixels associated with the missed points isformed. The missed points are suitably disposed into a 2D image, suchthat 2-dimension distance between positions of two missed points in the2D image is determined based on a 3D distance between the two missedpoints in the point cloud. In some examples, the geometry and colorvalues of the missed points are put into two separate images. In anexample, a Kd-tree is created over the missed points and the missedpoints are scanned to form 1D signals based on the nearest neighborhoodcriteria. The scanning result includes a geometry signal and a colorsignal that are respectively one dimensional. For example, the missedpoints are sorted according to the scan of the Kd-tree based on thenearest neighborhood criteria. The geometry signal includes a sequenceof geometry samples for the sorted missed points, and the color signalincludes a sequence of color values for the sorted missed points. Thesamples in the 1D signals are disposed to form 2D images, such as ageometry image, a color image, and the like according to a scan order,such as the scan order shown in FIG. 8 and FIG. 9.

At (S1130), the image is encoded using suitable compression tools. Forexample, the geometry image and the color image are respectivelyencoded.

At (S1140), a coded bitstream that includes the encoded image for themissed points is formed. In some embodiments, flags that are indicativethe order to arrange the 1D signals into the 2D images can be includedin the coded bitstream. Then, the process proceeds to (S1199) andterminates.

FIG. 12 shows a flow chart outlining a process (1200) according to anembodiment of the disclosure. The process (1200) can be used during adecoding process for reconstructing point clouds. In variousembodiments, the process (1200) is executed by processing circuitry,such as the processing circuitry in the terminal devices (120), theprocessing circuitry that performs functions of the decoder (210), theprocessing circuitry that performs functions of the decoder (400), andthe like. In some embodiments, the process (1200) is implemented insoftware instructions, thus when the processing circuitry executes thesoftware instructions, the processing circuitry performs the process(1200). The process starts at (S1201) and proceeds to (S1210).

At (S1210), prediction information of an image is decoded from a codedbitstream corresponding to a point cloud. The prediction informationindicates that the image includes missed points from patches for thepoint cloud, and the missed points are arranged in the image accordingto a non-jumpy scan. In an embodiment, flags and parameters are decodedfrom coded bitstream, such as the syntax shown in FIG. 10. The flags canindicate the non-jumpy scan.

At (S1220), the missed points are reconstructed from the image accordingto the non-jumpy scan. In an example, the flags indicate a non-jumpyhorizontal raster scan order as shown in FIG. 8. Then, when the image isdecoded, the missed points can be reconstructed according to thenon-jumpy horizontal raster scan order as shown in FIG. 8. In anotherexample, the flags indicate a block based non-jumpy horizontal rasterscan order shown in FIG. 9. Then, when the image is decoded, the missedpoints can be reconstructed according to the block based non-jumpyhorizontal raster scan order as shown in FIG. 9. Then, the processproceeds to (S1299) and terminates.

The techniques described above, can be implemented as computer softwareusing computer-readable instructions and physically stored in one ormore computer-readable media. For example, FIG. 13 shows a computersystem (1300) suitable for implementing certain embodiments of thedisclosed subject matter.

The computer software can be coded using any suitable machine code orcomputer language, that may be subject to assembly, compilation,linking, or like mechanisms to create code comprising instructions thatcan be executed directly, or through interpretation, micro-codeexecution, and the like, by one or more computer central processingunits (CPUs), Graphics Processing Units (GPUs), and the like.

The instructions can be executed on various types of computers orcomponents thereof, including, for example, personal computers, tabletcomputers, servers, smartphones, gaming devices, internet of thingsdevices, and the like.

The components shown in FIG. 13 for computer system (1300) are exemplaryin nature and are not intended to suggest any limitation as to the scopeof use or functionality of the computer software implementingembodiments of the present disclosure. Neither should the configurationof components be interpreted as having any dependency or requirementrelating to any one or combination of components illustrated in theexemplary embodiment of a computer system (1300).

Computer system (1300) may include certain human interface inputdevices. Such a human interface input device may be responsive to inputby one or more human users through, for example, tactile input (such as:keystrokes, swipes, data glove movements), audio input (such as: voice,clapping), visual input (such as: gestures), olfactory input (notdepicted). The human interface devices can also be used to capturecertain media not necessarily directly related to conscious input by ahuman, such as audio (such as: speech, music, ambient sound), images(such as: scanned images, photographic images obtain from a still imagecamera), video (such as two-dimensional video, three-dimensional videoincluding stereoscopic video).

Input human interface devices may include one or more of (only one ofeach depicted): keyboard (1301), mouse (1302), trackpad (1303), touchscreen (1310), data-glove (not shown), joystick (1305), microphone(1306), scanner (1307), camera (1308).

Computer system (1300) may also include certain human interface outputdevices. Such human interface output devices may be stimulating thesenses of one or more human users through, for example, tactile output,sound, light, and smell/taste. Such human interface output devices mayinclude tactile output devices (for example tactile feedback by thetouch-screen (1310), data-glove (not shown), or joystick (1305), butthere can also be tactile feedback devices that do not serve as inputdevices), audio output devices (such as: speakers (1309), headphones(not depicted)), visual output devices (such as screens (1310) toinclude CRT screens, LCD screens, plasma screens, OLED screens, eachwith or without touch-screen input capability, each with or withouttactile feedback capability—some of which may be capable to output twodimensional visual output or more than three dimensional output throughmeans such as stereographic output; virtual-reality glasses (notdepicted), holographic displays and smoke tanks (not depicted)), andprinters (not depicted).

Computer system (1300) can also include human accessible storage devicesand their associated media such as optical media including CD/DVD ROM/RW(1320) with CD/DVD or the like media (1321), thumb-drive (1322),removable hard drive or solid state drive (1323), legacy magnetic mediasuch as tape and floppy disc (not depicted), specialized ROM/ASIC/PLDbased devices such as security dongles (not depicted), and the like.

Those skilled in the art should also understand that term “computerreadable media” as used in connection with the presently disclosedsubject matter does not encompass transmission media, carrier waves, orother transitory signals.

Computer system (1300) can also include an interface to one or morecommunication networks. Networks can for example be wireless, wireline,optical. Networks can further be local, wide-area, metropolitan,vehicular and industrial, real-time, delay-tolerant, and so on. Examplesof networks include local area networks such as Ethernet, wireless LANs,cellular networks to include GSM, 3G, 4G, 5G, LTE and the like, TVwireline or wireless wide area digital networks to include cable TV,satellite TV, and terrestrial broadcast TV, vehicular and industrial toinclude CANBus, and so forth. Certain networks commonly require externalnetwork interface adapters that attached to certain general purpose dataports or peripheral buses (1349) (such as, for example USB ports of thecomputer system (1300)); others are commonly integrated into the core ofthe computer system (1300) by attachment to a system bus as describedbelow (for example Ethernet interface into a PC computer system orcellular network interface into a smartphone computer system). Using anyof these networks, computer system (1300) can communicate with otherentities. Such communication can be uni-directional, receive only (forexample, broadcast TV), uni-directional send-only (for example CANbus tocertain CANbus devices), or bi-directional, for example to othercomputer systems using local or wide area digital networks. Certainprotocols and protocol stacks can be used on each of those networks andnetwork interfaces as described above.

Aforementioned human interface devices, human-accessible storagedevices, and network interfaces can be attached to a core (1340) of thecomputer system (1300).

The core (1340) can include one or more Central Processing Units (CPU)(1341), Graphics Processing Units (GPU) (1342), specialized programmableprocessing units in the form of Field Programmable Gate Areas (FPGA)(1343), hardware accelerators for certain tasks (1344), and so forth.These devices, along with Read-only memory (ROM) (1345), Random-accessmemory (1346), internal mass storage such as internal non-useraccessible hard drives, SSDs, and the like (1347), may be connectedthrough a system bus (1348). In some computer systems, the system bus(1348) can be accessible in the form of one or more physical plugs toenable extensions by additional CPUs, GPU, and the like. The peripheraldevices can be attached either directly to the core's system bus (1348),or through a peripheral bus (1349). Architectures for a peripheral businclude PCI, USB, and the like.

CPUs (1341), GPUs (1342), FPGAs (1343), and accelerators (1344) canexecute certain instructions that, in combination, can make up theaforementioned computer code. That computer code can be stored in ROM(1345) or RAM (1346). Transitional data can be also be stored in RAM(1346), whereas permanent data can be stored for example, in theinternal mass storage (1347). Fast storage and retrieve to any of thememory devices can be enabled through the use of cache memory, that canbe closely associated with one or more CPU (1341), GPU (1342), massstorage (1347), ROM (1345), RAM (1346), and the like.

The computer readable media can have computer code thereon forperforming various computer-implemented operations. The media andcomputer code can be those specially designed and constructed for thepurposes of the present disclosure, or they can be of the kind wellknown and available to those having skill in the computer software arts.

As an example and not by way of limitation, the computer system havingarchitecture (1300), and specifically the core (1340) can providefunctionality as a result of processor(s) (including CPUs, GPUs, FPGA,accelerators, and the like) executing software embodied in one or moretangible, computer-readable media. Such computer-readable media can bemedia associated with user-accessible mass storage as introduced above,as well as certain storage of the core (1340) that are of non-transitorynature, such as core-internal mass storage (1347) or ROM (1345). Thesoftware implementing various embodiments of the present disclosure canbe stored in such devices and executed by core (1340). Acomputer-readable medium can include one or more memory devices orchips, according to particular needs. The software can cause the core(1340) and specifically the processors therein (including CPU, GPU,FPGA, and the like) to execute particular processes or particular partsof particular processes described herein, including defining datastructures stored in RAM (1346) and modifying such data structuresaccording to the processes defined by the software. In addition or as analternative, the computer system can provide functionality as a resultof logic hardwired or otherwise embodied in a circuit (for example:accelerator (1344)), which can operate in place of or together withsoftware to execute particular processes or particular parts ofparticular processes described herein. Reference to software canencompass logic, and vice versa, where appropriate. Reference to acomputer-readable media can encompass a circuit (such as an integratedcircuit (IC)) storing software for execution, a circuit embodying logicfor execution, or both, where appropriate. The present disclosureencompasses any suitable combination of hardware and software.

APPENDIX A: ACRONYMS

JEM: joint exploration model

VVC: versatile video coding

BMS: benchmark set

MV: Motion Vector

HEVC: High Efficiency Video Coding

SEI: Supplementary Enhancement Information

VUI: Video Usability Information

GOPs: Groups of Pictures

TUs: Transform Units,

PUs: Prediction Units

CTUs: Coding Tree Units

CTBs: Coding Tree Blocks

PBs: Prediction Blocks

HRD: Hypothetical Reference Decoder

SNR: Signal Noise Ratio

CPUs: Central Processing Units

GPUs: Graphics Processing Units

CRT: Cathode Ray Tube

LCD: Liquid-Crystal Display

OLED: Organic Light-Emitting Diode

CD: Compact Disc

DVD: Digital Video Disc

ROM: Read-Only Memory

RAM: Random Access Memory

ASIC: Application-Specific Integrated Circuit

PLD: Programmable Logic Device

LAN: Local Area Network

GSM: Global System for Mobile communications

LTE: Long-Term Evolution

CANBus: Controller Area Network Bus

USB: Universal Serial Bus

PCI: Peripheral Component Interconnect

FPGA: Field Programmable Gate Areas

SSD: solid-state drive

IC: Integrated Circuit

CU: Coding Unit

While this disclosure has described several exemplary embodiments, thereare alterations, permutations, and various substitute equivalents, whichfall within the scope of the disclosure. It will thus be appreciatedthat those skilled in the art will be able to devise numerous systemsand methods which, although not explicitly shown or described herein,embody the principles of the disclosure and are thus within the spiritand scope thereof.

What is claimed is:
 1. A method for point cloud decompression,comprising: decoding, by a processor, prediction information of an imagefrom a coded bitstream corresponding to a point cloud, the predictioninformation indicating that the image includes a plurality of missedpoints from at least a patch for the point cloud, and the plurality ofmissed points are arranged in the image according to a non-jumpy scan;and reconstructing, by the processor, the plurality of missed pointsfrom the image according to the non-jumpy scan.
 2. The method of claim1, further comprising: reconstructing, by the processor, a first missedpoint as a last pixel in a first row, and a second missed point that isnext to the first missed point as a first pixel in a second row, thelast pixel in the first row and the first pixel in the second row beingin a same column.
 3. The method of claim 1, further comprising:decoding, by the processor, a flag associated with the image, the flagbeing indicative of the non-jumpy scan.
 4. The method of claim 1,further comprising: decoding, by the processor, a flag that isindicative of a block based non-jumpy scan; and decoding, by theprocessor, a block size for the block based non-jumpy scan.
 5. Themethod of claim 4, further comprising: dividing, by the processor, theimage into blocks according to the block size; and reconstructing, bythe processor, missed points within a block according to the non-jumpyscan.
 6. The method of claim 5, further comprising: reconstructing, bythe processor, a first missed point as a last pixel in a first row ofthe block, and a second missed point that is adjacent to the firstmissed point as a first pixel in a second row of the block, the lastpixel in the first row and the first pixel in the second row being in asame column.
 7. The method of claim 5, further comprising: processing,by the processor, the blocks in an order according to the non-jumpy scanof the blocks.
 8. A method for point cloud compression, comprising:determining, by a processor, a plurality of missed points from at leasta patch of a point cloud; forming, by the processor, an image withpixels associated with the plurality of missed points, a 2-dimensiondistance between positions of two missed points in the image beingdetermined based on a 3-dimension distance between the two missed pointsin the point cloud; encoding the image; and forming a coded bitstreamthat includes the encoded image.
 9. The method of claim 8, furthercomprising: ordering, by the processor, the plurality of missed pointsinto a list of missed points based on a nearest neighbor criterion;associating, by the processor, the list of missed points to the pixelsof the image according to a non-jumpy scan.
 10. The method of claim 9,further comprising: associating, by the processor, a first missed pointto a last pixel in a first row of the image; and associating, by theprocessor, a second missed point that is next to the first missed pointin the list of missed points to a first pixel in a second row of theimage, the last pixel in the first row and the first pixel in the secondrow being in a same column.
 11. The method of claim 9, furthercomprising: associating, by the processor, a first missed point to alast pixel in a first row of a block in the image; and associating, bythe processor, a second missed point that is next to the first missedpoint in the list of missed points to a first pixel in a second row ofthe block in the image, the last pixel in the first row and the firstpixel in the second row being in a same column.
 12. The method of claim9, further comprising: including a flag indicative of the non-jumpy scanin the coded bitstream.
 13. The method of claim 11, further comprising:including a block size in the coded bitstream.
 14. An apparatus forpoint cloud decompression, comprising: processing circuitry configuredto: decode prediction information of an image from a coded bitstreamcorresponding to a point cloud, the prediction information indicatingthat the image includes a plurality of missed points from at least apatch for the point cloud, and the plurality of missed points arearranged in the image according to a non-jumpy scan; and reconstruct theplurality of missed points from the image according to the non-jumpyscan.
 15. The apparatus of claim 14, wherein the processing circuitry isconfigured to: reconstruct a first missed point as a last pixel in afirst row, and a second missed point that is next to the first missedpoint as a first pixel in a second row, the last pixel in the first rowand the first pixel in the second row being in a same column.
 16. Theapparatus of claim 14, wherein the processing circuitry is configuredto: decode a flag associated with the image, the flag being indicativeof the non-jumpy scan.
 17. The apparatus of claim 14, wherein theprocessing circuitry is configured to: decode a flag that is indicativeof a block based non-jumpy scan; and decode a block size for the blockbased non-jumpy scan.
 18. The apparatus of claim 17, wherein theprocessing circuitry is configured to: divide the image into blocksaccording to the block size; and reconstruct missed points within ablock according to the non-jumpy scan.
 19. The apparatus of claim 18,wherein the processing circuitry is configured to: reconstruct a firstmissed point as a last pixel in a first row of the block, and a secondmissed point that is next to the first missed point as a first pixel ina second row of the block, the last pixel in the first row and the firstpixel in the second row being in a same column.
 20. The apparatus ofclaim 18, wherein the processing circuitry is configured to: process theblocks in an order according to the non-jumpy scan of the blocks.